Distributed wireless monitoring systems have many important applications including deployment in third-world communities that currently lack access to safe drinking water and/or use biomass for their daily energy needs. Remote monitoring systems are a useful method to ensure the success of water, energy and infrastructure projects conducted in their communities. Rather than infrequent human measurement, remote monitoring systems deployed in these communities automatically make measurements and ensure that community partnerships are maintained.
Current distributed wireless monitoring systems typically take one of four approaches to data logging. In one approach, sensor data is logged at specific scheduled times or intervals (e.g., every 15 minutes). Another approach logs a data point whenever a monitored cumulative usage meets a predetermined value (e.g., upon each gallon of water flow past the sensor). Other approaches detect a discrete change in state, and the logger records a timestamp or duration since the last change in state. In another approach, the data logger is a counter that simply logs a total number of discrete events.
Current distributed wireless monitoring systems experience a tradeoff between frequency of sampling/logging and energy consumption. On the one hand, in many applications it is beneficial to have plentiful data reported at frequent intervals. On the other hand, data sampling, logging, and wireless transmission all consume power which is limited in battery operated remote sensor devices. Unfortunately, current systems use remote sensor devices that are not power efficient because they are built of components (sensors, microprocessor, logger, radio, antenna, and power supply) that are packaged and sold separately. In view of these and other problems with existing distributed wireless monitoring systems, it would be an advance in the art to provide improved distributed wireless monitoring systems that address these problems.